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Chinese Automation Congress (CAC)

作者： Shuai Cao Jie Yu Xingyu Fan Qiuhao Zhang Fangjia Xue Dibo Hou State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University Hangzhou China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

In the application of three-dimensional (3-D) fluorescence spectroscopy for river water pollutant detection, traditional feature extraction models often neglect wavelength information and complex intermolecular interrelationships. Moreover, experiments are frequently limited to single-substance classifications. This research addresses these limitations by proposing a novel model for organic pollutant recognition based on graph neural networks (GNNs). The proposed method begins by using the excitation-emission matrix and the wavelength information corresponding to each fluorescence intensity value as inputs. A convolutional neural network (CNN) is initially employed to extract preliminary features from the three-dimensional fluorescence spectra. Subsequently, the initial spectral features obtained during the pre-training stage are used to construct a graph neural network model. This model represents each category of organic pollutants as nodes within the graph, capturing the intrinsic connections between different pollution samples through node interactions. Finally, the model outputs a score vector for each category to classify the pollutants. To validate the proposed model, datasets comprising twelve common organic pollutants, both as single substances and mixtures, were collected. Comparative analysis with other methods demonstrates that the proposed approach achieves a high accuracy rate.

关键词： Volatile organic compounds Accuracy Water quality Fluorescence Feature extraction Water pollution Vectors Rivers Monitoring Active matrix organic light emitting diodes

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Development of a Compact Optical Layout for a Miniature Fluorescence Spectrometer: In-Situ Detection of Organic Pollutants in Aquatic Environment

Development of a Compact Optical Layout for a Miniature Fluo...

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Chinese Automation Congress (CAC)

作者： Xingyu Fan Jie Yu Qiuhao Zhang Shuai Cao Lingke Zhang Fangjia Xue State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University Hangzhou China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

In recent years, the increasing presence of emerging organic pollutants in rivers, lakes, and other aquatic environments has posed significant threats to human health and ecological safety. Current monitoring technologies for these pollutants face several challenges, including the high cost of equipment and the scarcity of trained professionals. Furthermore, existing portable fluorescence sensors are limited by inadequate data, unsuitability for in-situ water environments, and the ability to detect only specific pollutants. This paper proposes a novel design for an in-situ miniature fluorescence spectrometer, utilizing a compact optical layout to monitor organic pollutants in water. The design features a high-power UV LED combined with a lens group to enhance the fluorescence excitation effect of low-concentration organic pollutants. The system components are integrated into a compact layout centered around a flow cell, significantly reducing the device's size. In experimental validation, vitamin B was used as a model organic pollutant to test the prototype's detection capabilities. Within the concentration range of 1 − 100 μg/L, the fluorescence intensity exhibited a strong linear correlation with the vitamin B concentration, achieving an R 2 value of 0.9945, comparable to that of commercial spectrometers. This portable device demonstrates excellent performance in detecting organic matter and offers significant advantages for in-situ monitoring applications, making it well-suited for real-time pollutant detection in rivers, lakes, and other aquatic environments.

关键词： Performance evaluation Optical design Layout Prototypes Fluorescence Light emitting diodes Water pollution Rivers Optical sensors Monitoring

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Improved Residual Reinforcement Learning for Dynamic Obstacle Avoidance of Robotic Arm

Improved Residual Reinforcement Learning for Dynamic Obstacl...

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Data Driven control and Learning Systems (DDCLS)

作者： Zhenting Liu Shan Liu State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University Hangzhou China

ISBN: (数字)9798350361674

ISBN: (纸本)9798350361681

This paper proposes an improved residual deep reinforcement learning method for robot arm dynamic obstacle avoidance and position servo. The proposed method first simplifies the state space by constructing key points and pre-trains a model capable of completing obstacle avoidance tasks using the simplified state. Then, when training with real state information, a guiding network is used to help accumulate good samples, which improves the training efficiency. To overcome the convergence difficulty of residual DQN in robot arm obstacle avoidance, this paper incorporates the action of the feedback controller into the action space and uses incremental reward values to evaluate the actions. Simulation results demonstrate that the proposed method can effectively achieve robot arm dynamic obstacle avoidance and position servo.

关键词： Training Learning systems Simulation Aerospace electronics Manipulators Deep reinforcement learning Collision avoidance

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Torsional Vibration Suppression Method Design for Variable-Speed Wind Turbine Based on UIO-SMC 22

Torsional Vibration Suppression Method Design for Variable-S...

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22nd IEEE International Conference on industrial Informatics, INDIN 2024

作者： Yu, Jiajun Xia, Jinhui Su, Jinya Li, Ze Huang, Wentao The School of Automation Southeast University Nanjing210096 China The State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University Hangzhou310058 China The College of Electronic and Information Engineering Hebei University Baoding071002 China The School of Internet of Things Engineering Jiangnan University Wuxi214122 China

ISBN: (纸本)9798331527471

With the continuous development of the wind power industry, variable-speed wind turbines (VSWT) are moving towards large-scale, and their applications have been expanded to offshore areas. However, the operating environment of offshore wind farm is even more harsh, and the potential torsional vibration of the drivetrain caused by disturbances in the offshore wind farm may introduce fatigue damage to the VSWT, resulting in unexpected faults that may lead to prolonged shutdown of the VSWT and loss of power generation efficiency. This study proposes a torsional vibration suppression strategy based on unknown input observer and sliding mode control. The proposed suppression strategy provides an appropriate electromagnetic torque compensation for the generator to mitigate disturbances in the whole control system. The effectiveness of the proposed strategy is validated by extensive simulation studies. © 2024 IEEE.

关键词： Sliding mode control

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Tomographic Object Detection by Unsupervised Clustering

Tomographic Object Detection by Unsupervised Clustering

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computer, Vision and Intelligent Technology (ICCVIT), International Conference on

作者： Fengyuan Wang Zheng Wang Yimin Wu Yandan Jiang Haifeng Ji Baoliang Wang State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University Hangzhou China

ISBN: (数字)9798331540043

ISBN: (纸本)9798331540050

This work introduces clustering to electrical tomography (ET) and first compares the effectiveness of different unsupervised clustering categories in tomographic object detection. First, the one-step linear back projection (LBP) algorithm is applied to reconstruct a rough image. Then, clustering is introduced to detect and refine the objects in the image, and a higher-quality image is obtained based on the clustering results. Six unsupervised clustering algorithms belonging to different categories, including K-means, Mini Batch K-means, Agglomerative, density peak clustering (DPC), statistical information grid (STING), gaussian mixture model (GMM), are compared from the aspects of clustering evaluation index, reconstruction quality and reconstruction efficiency. Simulation was carried out based on a capacitively coupled electrical resistance tomography (CCERT) system to collect the projection data under the cases of one to three objects to be detected in the sensing region. The research results show that the quality of object detection and reconstruction can be effectively improved by post-processing the image with clustering. It is found that for the single-object distribution, the grid-based clustering algorithm STING provides images with the highest quality. While for the multi-objects distributions (two or three objects), the Agglomerative algorithm belonging to the hierarchy clustering category shows advantage in achieving good images. Concerning the real-time performance, Agglomerative clustering algorithm is also preferred with less computational time than most of the other clustering algorithms. Therefore, among the combinations investigated in this work, LBP + Agglomerative clustering has the overall best performance in topographic object detection, in regarding of the reconstruction quality and efficiency.

关键词： Image quality Resistance Clustering algorithms Object detection Tomography Real-time systems Sensors Pattern recognition Indexes Image reconstruction

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Design and Analysis of Polynomial Positive Fuzzy System controllers Based on Markov Transitions

Design and Analysis of Polynomial Positive Fuzzy System Cont...

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Chinese Automation Congress (CAC)

作者： Sen Chang Xiaomiao Li Fucai Liu Zhiyong Bao Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University Qinhuangdao China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

This study explores polynomial Markov positive fuzzy systems, formulating controllers for these systems by examining the prerequisites for positivity and stochastic stability. Initially, polynomials are incorporated into the Markov positive fuzzy system to represent nonlinear elements better and enhance its capacity to model nonlinear systems. Concurrently, the study discusses the non-convex scenarios encountered in the stability analysis of the closed-loop system once the positive fuzzy system controller is integrated and confirms the stability of the Markov polynomial positive fuzzy system. Ultimately, the effectiveness of the proposed approaches is demonstrated through a numerical simulation example.

关键词： Automation Stochastic processes Numerical simulation Stability analysis Polynomials Numerical models Closed loop systems Nonlinear systems Numerical stability Fuzzy systems

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Mitigating household air pollution exposure through kitchen renovation

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Environmental Science and Ecotechnology 2025年第1期23卷 175-182页

作者： Yatai Men Ke Jiang Yaoji Li Ran Xing Zhihan Luo Tianyao Huang Shuyu Ou'yang Wei Du Yuanchen Chen Guofeng Shen MOE Key Lab for Earth Surface Process College of Urban and Environmental SciencesPeking UniversityBeijing100871China Yunnan Provincial Key Laboratory of Soil Carbon Sequestration and Pollution Control Faculty of Environmental Science&EngineeringKunming University of Science&TechnologyKunming650500China Southwest United Graduate School Kunming650092China Key Laboratory of Microbial Technology for Industrial Pollution Control of Zhejiang Province College of Environment Research Center of Environmental ScienceZhejiang University of TechnologyHangzhou310032China Institute of Carbon Neutrality Peking UniversityBeijing100871China

Globally,over three billion people rely on traditional solid fuels for cooking and heating,leading to significant household air pollution and critical public health *** transitioning to clean energy carriers faces challenges of accessibility and affordabilitydespecially among low-income,rural populationsdalternative strategies like kitchen layout modifications and the use of ventilation fans may effectively reduce exposure to ***,we analyze factors influencing the adoption of separated kitchens and mechanical ventilation and evaluate changes in human exposure to PM2.5 under different kitchen renovation scenarios by conducting a nationwide survey of household kitchen characteristics in rural *** found that although 82%of rural households have kitchens separated from other rooms,only 34%use mechanical *** adoption of ventilation fans is significantly influenced by income and education *** estimate that widespread implementation of ventilation fans and separated kitchen designs could prevent approximately 67400 premature deaths annually,resulting in a health benefit of about USD 19 billion per yeardsubstantially exceeding the costs *** findings suggest that cost-effective kitchen renovations offer enormous potential for substantial health benefits and present a practical solution compared to the challenges of clean energy transitions in rural areas.

关键词： Separating kitchen Mechanical ventilation Household air pollution Health benefits

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A Study of Structured Surface Generation on Tungsten Carbide by Electrical Discharge Machining with Self-assemble Ball Electrodes 38

A Study of Structured Surface Generation on Tungsten Carbide...

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38th Annual Meeting of the American Society for Precision engineering, ASPE 2023

作者： Li, Kangsen Cheung, Chi Fai Wang, Chunjin Gong, Feng State key Laboratory of Ultra-precision Machining Technology Department of Industrial and Systems Engineering Hongkong Polytechnic University Hong Kong Hong Kong Shenzhen Key Laboratory of High Performance Nontraditional Manufacturing College of Mechatronics and Control Engineering Shenzhen University Guangdong Shenzhen China

ISBN: (纸本)9781887706599

Electrical discharge machining (EDM) has been extensively utilized in the precision manufacturing of difficult-to-cut material. The preparation of electrodes is of great importance for structured surface generation after EDM. Electrode wear is an inevitable problem, which affects the machining accuracy and efficiency of the workpiece. Therefore, the design and optimization of the electrodes are vital for the EDM process. In this paper, a novel self-assembly ball electrode for EDM of the structured array on the binderless tungsten carbide (WC) is proposed. The shape evolution and surface roughness of the structured surface was investigated. The result indicates that self-assembly ball electrodes have a great advantage in machining the structured surface arrays. © 2023 Proceedings - ASPE 2023 Annual Meeting. All rights reserved.

关键词： Tungsten carbide

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Online Learning-Based Offloading Decision and Resource Allocation in Mobile Edge Computing-Enabled Satellite-Terrestrial Networks

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China Communications 2024年第3期21卷 230-246页

作者： Tong Minglei Li Song Han Wanjiang Wang Xiaoxiang School of Information and Communication Engineering Beijing University of Posts and TelecommunicationsBeijing 100876China Key Laboratory of Universal Wireless Communications Ministry of EducationBeijing University of Posts and TelecommunicationsBeijing 100876China School of Information and Control Engineering China University of Mining and TechnologyXuzhou 221116China School of Computer Science(National Pilot Software Engineering School) Beijing University of Posts and TelecommunicationsBeijing 100876China

Mobile edge computing(MEC)-enabled satellite-terrestrial networks(STNs)can provide Internet of Things(IoT)devices with global computing ***,the network state information is uncertain or *** deal with this situation,we investigate online learning-based offloading decision and resource allocation in MEC-enabled STNs in this *** problem of minimizing the average sum task completion delay of all IoT devices over all time periods is *** decompose this optimization problem into a task offloading decision problem and a computing resource allocation problem.A joint optimization scheme of offloading decision and resource allocation is then proposed,which consists of a task offloading decision algorithm based on the devices cooperation aided upper confidence bound(UCB)algorithm and a computing resource allocation algorithm based on the Lagrange multiplier *** results validate that the proposed scheme performs better than other baseline schemes.

关键词： computing resource allocation mobile edge computing satellite-terrestrial networks task offloading decision

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Optimizing Indoor Network Element Layout for Enhanced Signal Coverage and Security in Location-Based Services 7th

Optimizing Indoor Network Element Layout for Enhanced Signa...

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7th International Conference on Attacks and Defenses for Internet-of-Things, ADIoT 2024

作者： Yu, Xiaomin Yu, Xiaokun College of Computer and Control Engineering Qiqihar University Qiqihar China Heilongjiang Key Laboratory of Big Data Network Security Detection and Analysis Qiqihar University Qiqihar China Heilongjiang Jiaotong Polytechnic Qiqihar China

ISBN: (纸本)9783031855924

Recently, with the rapid development of communication technology, location-based services (LBS) in indoor environments have penetrated into various aspects of people’s daily lives. Wireless local area networks (WLAN) have become the preferred choice for location-based services due to their broad deployment and low cost. However, the typical non-line-of-sight characteristics of indoor environments result in severe fluctuations in received signal strength (RSS), signal coverage vulnerabilities can exacerbate environmental interference, making positioning results more vulnerable to attacks or tampering. The layout of indoor network elements is a key factor that constrains signal coverage rate. This paper focuses on the optimization of indoor network element layout, proposes an indoor network element layout optimization model based on signal coverage and quality in indoor environments and introduces an Adaptive Simulation Annealing Non-inertial Opposite Particle Swarm Optimization algorithm (ASA-NRPSO). Firstly, a reverse strategy is introduced into the particle flight process of the Particle Swarm Optimization (PSO) algorithm, and high-quality particles are selected for the next generation iteration. In the selection of the reverse strategy, the simulated annealing idea is integrated to adaptively select the reverse strategy based on the needs of the particles at different stages, which avoids the particles falling into local optima. The inertia term in the particle swarm velocity update formula is replaced with group information for non-inertial updates. This can more fully utilize the global information of the population to guide the movement of the next generation of particles and improve the convergence speed of the particle swarm. The elite mutation strategy is used to increase the diversity of particles and improve the global search capability of the algorithm. This method ensures the rapid generation of network element layout to improve the signal coverage rate

关键词： Location based services

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